SLP/BUS520 Business Analytics And Decision Making Business Analytics & Intelligence Reporting Final Analysis **Complete Module 4 SLP before Module 4 Case** We have been working with survey data

BUS520 SLP 3

Trident University International

BUS520 Business Analytics and Decision Making

June 9, 2024

BUS 520 SLP 3

A correlation analysis is essential to determine the relation between different variables. The organizational commitment will be correlated to other factors like job satisfaction, as well as extrinsic and intrinsic factors. Such variables are essential to determine the commitment of employees toward their organization's growth.

Correlation: Organizational Commitment x Overall Job Satisfaction

(Table 1: Organizational Commitment x Overall Job Satisfaction correlation)

Based on the table above, the correlation coefficient is -0.01543, meaning that the numbers are very close to zero. This also means that there is a very poor and negligible relationship between the job satisfaction and commitment variables. (Asuero et al. 2006). Therefore, as the organizational commitment changes, the satisfaction levels in the organization remain the same.

(Figure 1: Organizational Commitment x Overall Job Satisfaction scatterplot)

From the scatterplot, we can observe a scattered distribution of data points, indicating a weak relationship between the two variables. The linear regression equation, y=−0.0182x+4.2083 further supports this finding. The negative slope of -0.0182 suggests that as as commitment is reduced by a single unit, the satisfaction is reduced by 0.0182, which is a very small change. This confirms the negligible relationship between the two variables, meaning that they do not significantly influence each other.

Correlation: Organizational Commitment x Intrinsic Job Satisfaction

(Table 2: Organizational Commitment x Intrinsic Job Satisfaction correlation)

The data above shows the correlation between commitment and intrinsic variables. The correlation coefficient is -0.04924, indicating poor linear relationship between the variables. (Ratner, 2009). The negative sign means that when there is an increase in commitment, the intrinsic satisfaction is reduced, although the relationship is weak. As commitment increases, employees may feel less satisfied with the intrinsic aspects of their job.

(Figure 2: Organizational Commitment x Intrinsic Job Satisfaction scatterplot)

The regression equation found on the graph is y=−0.062x+4.8335. Thus, the slope is -0.062. This means that when commitment increases by a single unit, the intrinsic is reduced by 0.062 units, which is a weak relation. This weak relation stresses the findings on the correlation table that the two variables are poorly related.

Correlation: Organizational Commitment x extrinsic Job Satisfaction

(Table 3: Organizational Commitment x extrinsic Job Satisfaction correlation)

The above correlation table shows the relationship between commitment and extrinsic satisfaction, which helps explain the relationship between variables. The correlation coefficient is -0.0467, which is a moderate linear relationship. The negative sign shows that as commitment increases, the extrinsic relationship reduces.

(Figure 3: Organizational Commitment x extrinsic Job Satisfaction scatterplot)

The equation found is y=−0.3769x+5.8049, meaning that the slope is -0/3769. This means that as commitment increases by a single unit, extrinsic reduces by 0.3769. This moderate relationship is stronger than the others discussed above, although it is not very strong.

Managerial Implications

Based on the correlations above, there is a weak relationship between intrinsic organizational commitment and job satisfaction. This means that when the management increases commitment, satisfaction levels will stay the same. Management should focus on other factors to increase satisfaction, such as better working environments, training, and career development. There should be a holistic approach towards other factors that increase satisfaction, which are not necessarily related to job satisfaction. (Robescu & Iancu 2016). Management should develop other intrinsic motivation features that are influenced by intrinsic motivation, such as personal growth and support in the workplace.

On the other hand, there is a moderate relationship between commitment and extrinsic satisfaction. Where commitment increases, there is a reduction in extrinsic motivation. This means management should look for factors other than commitment that increase motivation. For example, rewards and incentives should be provided to workers to be productive. Management would develop cultures geared towards advancing careers and recognition for outstanding performance, which is a sustainable way of boosting long-term commitment.

There are several factors that managers could implement in the organization; for example, worker engagement programs to promote career development and recognition. The management could develop individualized motivation methods since each employee is motivated by different factors. Examples are professional and personal development. The motivation could be geared towards addressing personal needs. Managers could also create a balanced reward system where external and internal motivation are gradually nurtured while supporting the needs and expectations of the employees in the organization. Companies should also have effective leadership strategies where employees are inspired to achieve organizational objectives based on individual expectations. Managers should also motivate employees through open communication, rewards, and walking the talk.

Conclusion

In conclusion, correlation analysis helps to understand the relationship and insights between various variables. Based on the analysis, there is a weak relation between commitment, intrinsic, and job satisfaction. Managers should develop individualized programs that understand each employee’s needs and motivate them to achieve better. Through feedback and effective leadership, employees are inspired to achieve more.

References

Asuero, A. G., Sayago, A., & González, A. G. (2006). The correlation coefficient: An overview. Critical reviews in analytical chemistry, 36(1), 41-59.

Ratner, B. (2009). The correlation coefficient: Its values range between 1/− 1, or do they? Journal of Targeting, measurement and analysis for marketing, 17(2), 139-142.

Robescu, O., & Iancu, A. G. (2016). The effects of motivation on employee's performance in organizations. Valahian Journal of Economic Studies, 7(2), 49-56.